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Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
Under the Conditions of Non-Agenda Ownership: Social Medi...
Artem Zakharchenko, Yuliia Maksimtsova, Valentyn Iurchenko, Vikt · 2019-09-04 · via cs.CR updates on arXiv.org

Owing to its history and challenging circumstances, social networks community in Ukraine is a very interesting polygon for the study of communications in the constantly changing environment, especially in the political discourse. This unique environment requires three dimensions to ascertain the political position of its participant. But 2019 presidential elections made this object even more spectacular. The winner of elections comedian Volodymyr Zelenskyi reached 73% of votes without any issue ownership, with empty agenda, and this influenced the electoral content of social networks and their authors behavior. We saw, that the issue ownership by other candidates succeeds in making their issues more salient in social networks. But the new phenomena, the non-agenda ownership, overcome any ideological influence, especially under the conditions of punishment mechanism applied to old politicians. Analyzing social media content and users behavior in the period between two rounds of elections, we found considerable overlaps between this campaign and the 2016 Trump campaign. We approved the widespread of filter bubbles, negative campaign messages, fake news and conspiracy theories. Active and powerful core of Ukrainian Facebook that was responsible for the Revolution of dignity now became less significant and even turns into the huge filter bubble of active people. We also proved that manipulations and fake news in the environment of private groups may be as much powerful as in a case of classical communication based around the opinion leaders.